Resilience is a key feature of ecosystem dynamics reflecting a system's ability to resist and recover from environmental perturbations. Slowing down in the rate of recovery has been used as an early-warning signal for abrupt transitions. Recent advances in Earth observation (EO) vegetation data provide the capability to capture broad-scale resilience patterns and identify regions experiencing resilience loss. However, the proliferation of methods for evaluating resilience using EO data has introduced significant uncertainty, leading to contradictory resilience estimates across approximately 73% of the Earth's land surface. To reconcile these perspectives, we review the range of methods and associated metrics that capture aspects of ecosystem resilience using EO data. Using a principal component analysis, we empirically test the relationships between the most widely used resilience metrics and explore emergent patterns within and among the world's biomes. Our analysis reveals that the 10 resilience metrics aggregate into four core components of ecosystem dynamics, highlighting the multidimensional nature of ecosystem resilience. We also find that ecosystems with slower recovery are more resistant to drought extremes. Furthermore, the relationships between resilience metrics vary across the world's biomes and vegetation types. These results illustrate the inherent differences in the dynamics of natural systems and highlight the need for careful consideration when evaluating broad-scale resilience patterns across biomes. Our findings provide valuable insights for identifying global resilience patterns, which are critically needed to inform policy decisions and guide conservation efforts globally.

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http://dx.doi.org/10.1111/gcb.70115DOI Listing

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